Biology subjects

Sen, E.

Publications and source records attributed to Sen, E..

6 recordsLinked to original sources

bioRxiv2026

Starvation modulates associative short-term memory of Drosophila in a task-dependent manner

It is widely believed that starvation favours the processing of food-related cues, a notion here called the adaptive specificity hypothesis. Indeed, in Drosophila melanogaster starvation is required for appetitive odour-sugar but not for aversive odour-shock memory. Results from Gruber et al. (2013) and Meschi et al. (2024), however, suggest that starvation improves aversive short-term memory, too, challenging this hypothesis. We survey how starvation affects Drosophila associative olfactory short-term memory across 26 learning tasks. These tasks differ in the reinforcers and the amount of training, the life stage of the animals, in the predictive structure and associative timing of the task, in whether memory is expressed as an increase or decrease in odour preference, and in whether the learned behaviour is motivated by obtaining reward or avoiding/ escaping punishment. In adult flies, an improvement was observed for appetitive odour-sugar memories, whereas all tasks yielding aversive memory were unaffected. Strikingly, appetitive tasks that are not sugar-related, namely odour-shock extinction learning and punishment-relief associations, were either unaffected or even impaired, supporting the adaptive specificity hypothesis. In contrast, in 5-day-old larvae sugar-related appetitive associations were compromised, and the same was observed, to varying degrees, in larvae starved one day earlier and for aversive quinine associations, challenging the adaptive specificity hypothesis. Furthermore, we observed starvation-induced changes in locomotion and preference for a subset of the cues used in our study. Our results defy a simplistic interpretation in terms of the adaptive specificity hypothesis and call for case-by-case analyses of how starvation affects learning and behaviour.

neuroscience↗

bioRxiv2026

Disagreement between demultiplexing methods reveals structured cell quality gradients in multiplexed single-cell data

BackgroundSingle-cell multi-omics profiling of hematopoietic malignancies frequently involves pooling of patient samples before library preparation to reduce costs. Demultiplexing and quality control of the resulting sequencing data depend on experimental design, sequencing depth, and computational methods. Existing approaches benchmark individual tools, auto-select a single best method, or apply majority voting. However, none systematically exploit disagreement patterns among orthogonal strategies as a diagnostic signal for cell quality. ResultsWe introduce Split-flow, a modular Nextflow pipeline that runs hashing-based and SNP-based demultiplexing, and transcriptome-based doublet detection in parallel. It classifies cells into quality strata through a concordance-based decision framework. Validation on multiplexed CITE-seq data from 14 multiple myeloma patients across eight Chromium channels demonstrates high reproducibility and shows that discordant cells cluster within specific cell types and quality strata. TCR clonotype cross-referencing against VDJdb confirms that concordance-based classification enriches for biologically genuine immune receptor sequences, with a 5.3-fold enrichment of confirmed public TCR sequences in the high-confidence stratum. Downsampling analysis reveals that SNP-based methods are more depth-sensitive than hash-based approaches, supporting the recommendation to combine both strategies. The framework transfers to AML samples across three assay types (snMultiome-seq, scRNA-seq, scATAC-seq), where ATAC-based demultiplexing resolves donor assignment discordance under low hashing efficiency. ConclusionsSplit-flow demonstrates that combining of orthogonal preprocessing methods yields structured information about cell quality and offers a concordance-based framework that transforms this disagreement into a diagnostic signal. It introduces a preprocessing approach that can be exploited beyond hematopoietic malignancies in multiplexed single-cell applications. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/724135v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1f36dbcorg.highwire.dtl.DTLVardef@a9799forg.highwire.dtl.DTLVardef@6fca94org.highwire.dtl.DTLVardef@15cc1f3_HPS_FORMAT_FIGEXP M_FIG C_FIG Highlights and main findingsO_LIIntroduces Split-flow, a modular Nextflow DSL2 pipeline for preprocessing of multiplexed single-cell multi-omics sequencing data from hematopoietic malignancy samples via a post hoc concordance-based decision framework. C_LIO_LIProvides practical guidance for the experimental design of multiplexed single-cell multi-omics experiments, including the recommendation to combine antibody-based hashing with a SNP genotype reference for orthogonal demultiplexing. C_LIO_LIReveals that SNP-based demultiplexing is more sensitive to sequencing depth than hash-based approaches, and that the combined strategy mitigates depth-dependent biases in cell-type recovery. C_LIO_LIDemonstrates that disagreement between demultiplexing methods contains structured diagnostic information about cell quality, with concordance categories reflecting genuine quality gradients in multiple myeloma CITE-seq samples. C_LIO_LIValidates the concordance framework using T cell receptor sequences as an orthogonal biological readout, with a 5.3-fold enrichment of confirmed public TCR sequences in the high-confidence stratum. C_LIO_LIApplies the preprocessing framework to AML patient samples across three assay types (snMultiome-seq, scRNA-seq, and scATAC-seq) and demonstrates that ATAC-based demultiplexing can resolve donor-assignment discordance. C_LI

bioinformatics↗

bioRxiv2025

Conserved programs and specificities of T cells targeting hematological malignancies

T cell-mediated immune surveillance is critical for cancer control, yet its endogenous effectiveness in hematological malignancies remains limited and poorly understood. Here, we integrate single-cell T cell receptor (TCR) profiling, HLA immunopeptidomics and functional antigen mapping to dissect the specificity landscape of bone marrow lymphocytes (BMLs) in multiple myeloma (MM) and acute myeloid leukemia (AML). We identify a rare subset of tumor-reactive T cells that exhibit a stereotyped transcriptional state distinct from bystander and virus-specific populations. Across both malignancies, immunopeptidomic profiling uncovers a partially conserved antigen repertoire enriched for noncanonical peptides, including products of novel or unannotated open reading frames (nuORFs), pseudogenes, and clonotypic immunoglobulin sequences. Several of these epitopes are recurrently presented and associated with convergent TCR responses across individuals. Based on this immune architecture, we develop a TCR-intrinsic fitness model that infers BML tumor specificity from transcriptional cues and stratifies immunotherapy response across three independent patient cohorts. Together, these findings map the latent potential of endogenous anti-tumor immunity in two biologically distinct diseases and provide a framework for decoding and restoring productive immune surveillance of hematological malignancies. HighlightsO_LISingle-cell resolved TCR profiling maps rare tumor-reactive T cells in the bone marrow of multiple myeloma (MM) and acute myeloid leukemia (AML) reveals conserved transcriptional programs C_LIO_LIA shared immunopeptidome across MM and AML includes noncanonical epitopes from nuORFs and idiotype sequences C_LIO_LIConserved tumor antigens elicit convergent T cell responses across patients C_LI O_LIA TCR fitness model predicts tumor specificity in bone marrow lymphocytes and stratifies immunotherapy response in both hematological malignancies C_LI

immunology↗

bioRxiv2024

Two distinct chromatin modules regulate proinflammatory gene expression

Various mechanisms have been proposed to explain gene activation and co-regulation, including enhancer-promoter interactions via chromatin looping and the enrichment of transcription factors into hubs or condensates. However, these conclusions often stem from analyses of individual loci, and genome-wide studies exploring mechanistic differences with coupled gene expression are lacking. In this study, we dissected the proinflammatory gene expression program induced by TNF in primary human endothelial cells using NGS- and imaging-based techniques. Our findings, enabled by our novel RWireX approach for single-cell ATAC-seq analysis, revealed two distinct regulatory chromatin modules: autonomous links of co-accessibility (ACs) between separated sites, and domains of contiguous co-accessibility (DCs) with increased local transcription factor binding. Genes in ACs and DCs exhibited different transcriptional bursting kinetics, highlighting the existence of two structurally and functionally distinct regulatory chromatin modules in the proinflammatory response. These findings provide a novel mechanistic framework for understanding how cells achieve rapid and precise gene expression control. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=71 SRC="FIGDIR/small/606159v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1f5f7e8org.highwire.dtl.DTLVardef@166b4d7org.highwire.dtl.DTLVardef@1ea9206org.highwire.dtl.DTLVardef@118d534_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LITwo distinct, non-mutually exclusive chromatin modules, ACs and DCs, that regulate proinflammatory gene expression were identified based on deep scATAC-seq. C_LIO_LIACs represent long-range genomic interactions with regulation occurring more by transcription burst frequency. C_LIO_LIDCs are regions of increased local transcription factor binding that can modulate transcription burst size. C_LIO_LIThe AC/DC model integrates sequencing-based evidence for chromatin looping with microscopy observations of transcription factor hubs/condensates into a unified model. C_LIO_LIOur findings provide a novel framework for understanding how cells achieve rapid and precise gene expression control. C_LI

genomics↗

bioRxiv2023

Cognitive limits of larval Drosophila: Testing for conditioned inhibition, sensory preconditioning and second-order conditioning

Drosophila larvae are an established model system for studying the mechanisms of innate and simple forms of learned behaviour. They have about 10 times fewer neurons than adult flies, and it was the low total number of their neurons that allowed for an electron microscopic reconstruction of their brain at synaptic resolution. Regarding the mushroom body, a central brain structure for associative learning in insects, it turned out that more than half of the classes of synaptic connection had previously escaped attention. Understanding the function of these circuit motifs, subsequently confirmed in adult flies, is an important current research topic. In this context, we test larval Drosophila for their cognitive abilities in three tasks that are characteristically more complex than those previously studied. Our data provide evidence for (i) conditioned inhibition, as has previously been reported for adult flies and honeybees. Unlike what is described for adult flies and honeybees, however, our data do not provide evidence for (ii) sensory preconditioning or (iii) second-order conditioning in Drosophila larvae. We discuss methodological features of our experiments as well as four specific aspects of the organisation of the larval brain that may explain why these two forms of learning are observed in honeybees and adult flies, but not in larval Drosophila.

animal behavior and cognition↗

bioRxiv2022

Rewarding capacity of optogenetically activating a giant GABAergic central-brain interneuron in larval Drosophila

Larvae of the fruit fly Drosophila melanogaster are a powerful study case for understanding the neural circuits underlying behavior. Indeed, the numerical simplicity of the larval brain has permitted the reconstruction of its synaptic connectome, and genetic tools for manipulating single, identified neurons allow neural circuit function to be investigated with relative ease and precision. We focus on one of the most complex neurons in the brain of the larva (of either sex), the GABAergic anterior paired lateral neuron (APL). Using behavioral and connectomic analyses, optogenetics, Ca2+ imaging and pharmacology, we study how APL affects associative olfactory memory. We first provide a detailed account of the structure, regional polarity, connectivity, and metamorphic development of APL, and further confirm that optogenetic activation of APL has an inhibiting effect on its main targets, the mushroom body Kenyon cells. All these findings are consistent with the previously identified function of APL in the sparsening of sensory representations. To our surprise, however, we found that optogenetically activating APL can also have a strong rewarding effect. Specifically, APL activation together with odor presentation establishes an odor-specific, appetitive, associative short-term memory, whereas naive olfactory behavior remains unaffected. An acute, systemic inhibition of dopamine synthesis as well as an ablation of the dopaminergic pPAM neurons impair reward learning through APL activation. Our findings provide a study case of complex circuit function in a numerically simple brain, and suggest a previously unrecognized capacity of central-brain GABAergic neurons to engage in dopaminergic reinforcement. Significance statementThe single, identified giant anterior paired lateral (APL) neuron is one of the most complex neurons in the insect brain. It is GABAergic and contributes to the sparsening of neuronal activity in the mushroom body, the memory center of insects. We provide the most detailed account yet of the structure of APL in larval Drosophila as a neurogenetically accessible study case. We further reveal that, contrary to expectations, the experimental activation of APL can exert a rewarding effect, likely via dopaminergic reward pathways. The present study both provides an example of unexpected circuit complexity in a numerically simple brain, and reports an unexpected effect of activity in central-brain GABAergic circuits.

neuroscience↗